Mango Dresses Up Its Mobile Results with Google Optimize 360
Customer Company Size
Large Corporate
Region
- Europe
Country
- Spain
Product
- Google Optimize 360
- Google Analytics 360
Tech Stack
- Google Analytics
- Google Optimize
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Supply Chain Visibility
- Retail Store Automation
Services
- Data Science Services
- System Integration
About The Customer
Mango is a global fashion retailer with a modern urban flair. The company opened its first store in Barcelona in 1984, and today Mango sells its stylish and affordable clothing in more than 2,200 stores across 111 countries, from Peru to Azerbaijan. Recently, Mango discovered a new challenge. Mobile visits to Mango’s online store were skyrocketing. In fact, the company’s Google Analytics 360 account revealed that 62% of all website traffic was coming in via mobile devices, a 50% increase year over year. Yet, despite these promising numbers, the team also discovered that the number of mobile transactions still lagged behind desktop transactions.
The Challenge
Mango, a global fashion retailer, was facing a challenge with its mobile platform. Despite a 50% year-over-year increase in mobile traffic, accounting for 62% of all website traffic, the number of mobile transactions was still lagging behind desktop transactions. The company wanted to improve the mobile shopping experience and increase the number of transactions on mobile devices. They needed to understand where users were in their path to purchase, including: opening a menu, searching for (and clicking on) a particular product, and choosing a shipping method. They also wanted to track exactly how many users reached each of these steps and see where users were exiting the purchase process.
The Solution
Mango used Google Analytics 360 to create several goals that would help identify where users were in their path to purchase. This provided greater insight into each stage of the mobile shopping experience and revealed areas for improvement. Based on the insights Mango discovered in Analytics 360, the team came up with new ideas for how they could improve the mobile shopping experience and increase the number of transactions on mobile devices. They used Google Optimize 360 to conduct website tests and track the entire customer experience across multiple devices, including mobile and tablet screens. The information they gathered allowed them to further enhance the mobile shopping process. They tested a simple change to the favorites icon offered to Mango mobile shoppers and the inclusion of an “Add” button in the product list page.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Case Study
Supermarket Energy Savings
The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.
